Hybrid motor vehicles are already known in the prior art and utilize two different drive motors that realize different drive concepts. As known from prevalent motor vehicles, on the one hand a combustion engine is thereby typically used that generates the drive power via combustion of fuel from a tank. In addition to the combustion engine, in a hybrid drivetrain an electric motor is also provided that can typically also work in a generative operation and is fed from a battery, typically a high voltage battery. A charging of the battery is also possible via the generative operation of the electric motor, for example via recuperation during a braking process and/or by diverting a portion of the power provided by the combustion engine. Also known in addition to this are what are known as plug-in hybrids, in which a charging device is provided via which the battery may also be charged from an electric grid or the like if the motor vehicle is parked.
Navigation systems with regard to motor vehicles have likewise already been known for a long time. They serve to direct a driver from a current position to a destination via corresponding driving instructions, consequently for route guidance. A route is thereby calculated that directs the motor vehicle to the destination. In order to calculate the optimal route to the destination, a cost function is typically used via which individual route segments—in particular road segments of a digital map—may be evaluated so that it is possible, for example, to realize the discovery of the optimal route as a directed tree search. The cost function consequently determines which optimization goals are considered, where typically multiple optimization goals are incorporated into the cost function with different weighting. Modern navigation systems therefore often have various modes that ultimately determine which optimization goal the driver considers most important. In a “fastest route” mode, for example, the optimal route is determined via which the driver of the motor vehicle most quickly reaches his destination. An analogous mode exists for a “shortest route”; in addition to this, recently modes have also become known that determine the most efficient route, in particular with regard to the consumption of the motor vehicle and/or its pollutant emissions. A vehicle model is thereby typically used that, for example, includes information about the consumption, the mass of the motor vehicle and the like, for example so that a route of least consumption may be set as an efficiency route, where naturally other efficiency criteria, for example an optimally low emission of pollutants, may also be set.
If a route to be driven has been determined, this is typically also transmitted—in particular in hybrid motor vehicles—to the drive control device controlling the components of the drivetrain, which drive control device uses the known future route in order to predictively plan and optimize a suitable operating strategy, in that predictive consumption on the selected route is determined in particular.
It is thereby problematic that, on the one hand, the navigation systems access the same input data set, in particular with regard to the mentioned vehicle model, for all motor vehicles in the determination of the optimal route. Details of specific motor vehicles are thus not taken into account. The current state of the hybrid motor vehicle, in particular of the drivetrain, is also considered in neither the determination of the optimal route nor the route guidance. Because the properties of the drivetrain, in particular with regard to the consumption, may change dynamically, in particular with regard to efficiency routes, it is not ensured that the ideal solution is always found. In particular, possibilities for charging the battery in hybrid motor vehicles can for the most part only be poorly planned in advance, or these do not enter at all into the determination of the efficiency route.